Literature DB >> 11522768

Evaluation of a computerized diagnostic decision support system for patients with pneumonia: study design considerations.

D Aronsky1, K J Chan, P J Haug.   

Abstract

Planning the clinical evaluation of a computerized decision support system requires a strategy that encompasses the different aspects of the clinical problem, the technical difficulties of software and hardware integration and implementation, the behavioral aspects of the targeted users, and the discipline of study design. Although clinical information systems are becoming more widely available, only a few decision support systems have been formally evaluated in clinical environments. Published accounts of difficulties associated with the clinical evaluation of decision support systems remain scarce. The authors report on a variety of behavioral, logistical, technical, clinical, cost, and work flow issues that they had to address when choosing a study design for a clinical trial for the evaluation of an integrated, real-time decision support system for the automatic identification of patients likely to have pneumonia in an emergency department. In the absence of a true gold standard, they show how they created a credible, clinically acceptable, and economical reference standard for the diagnosis of pneumonia, to determine the overall accuracy of the system. For the creation of a reference standard, they describe the importance of recognizing verification bias and avoiding it. Finally, advantages and disadvantages of different study designs are explored with respect to the targeted users and the clinical setting.

Entities:  

Mesh:

Year:  2001        PMID: 11522768      PMCID: PMC131045          DOI: 10.1136/jamia.2001.0080473

Source DB:  PubMed          Journal:  J Am Med Inform Assoc        ISSN: 1067-5027            Impact factor:   4.497


  27 in total

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  13 in total

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Journal:  Epidemiol Infect       Date:  2007-04-20       Impact factor: 2.451

3.  Translating clinical informatics interventions into routine clinical care: how can the RE-AIM framework help?

Authors:  Suzanne Bakken; Cornelia M Ruland
Journal:  J Am Med Inform Assoc       Date:  2009-08-28       Impact factor: 4.497

Review 4.  Interface, information, interaction: a narrative review of design and functional requirements for clinical decision support.

Authors:  Kristen Miller; Danielle Mosby; Muge Capan; Rebecca Kowalski; Raj Ratwani; Yaman Noaiseh; Rachel Kraft; Sanford Schwartz; William S Weintraub; Ryan Arnold
Journal:  J Am Med Inform Assoc       Date:  2018-05-01       Impact factor: 4.497

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Authors:  Karl J Madaras-Kelly; Richard E Remington; Kevin L Sloan; Vincent S Fan
Journal:  J Gen Intern Med       Date:  2012-03-07       Impact factor: 5.128

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Journal:  BMJ       Date:  2005-03-14

7.  "Similar query was answered earlier": processing of patient authored text for retrieving relevant contents from health discussion forum.

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Journal:  Health Inf Sci Syst       Date:  2019-02-18

Review 8.  The design of decisions: Matching clinical decision support recommendations to Nielsen's design heuristics.

Authors:  Kristen Miller; Muge Capan; Danielle Weldon; Yaman Noaiseh; Rebecca Kowalski; Rachel Kraft; Sanford Schwartz; William S Weintraub; Ryan Arnold
Journal:  Int J Med Inform       Date:  2018-05-21       Impact factor: 4.046

9.  An ontology-driven, diagnostic modeling system.

Authors:  Peter J Haug; Jeffrey P Ferraro; John Holmen; Xinzi Wu; Kumar Mynam; Matthew Ebert; Nathan Dean; Jason Jones
Journal:  J Am Med Inform Assoc       Date:  2013-03-23       Impact factor: 4.497

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Authors:  Dominik Aronsky; Evelyn Kasworm; Jay A Jacobson; Peter J Haug; Nathan C Dean
Journal:  J Am Med Inform Assoc       Date:  2004-06-07       Impact factor: 4.497

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